5 ms·

I too use Claude more frequently than OpenAi GPT4o. I think this is a two fold move for MS and I like it. Claude being more accurate / efficient for me says it'

I too use Claude more frequently than OpenAi GPT4o. I think this is a two fold move for MS and I like it. Claude being more accurate / efficient for me says it's likely they see the same thing, win number 1. The second is with all the OpenAI drama MS has started to distance themselves over a souring relationship (allegedly). If so, this could be a smart move away tactfully. Either way, Claude is great so this is a net win for everyone.

dartos 2y ago
Yeah, Claude consistently impresses me. A commenter on another thread mentioned it but it’s very similar to how search felt in the early 2000s. I ask it a question and get my answer. Sometimes it’s a little (or a lot) wrong or outdated, but at least I get something to tinker with.
- gonab 2y ago
  Conversely I feel that the experience of searching has been degraded by a lot since 2016/17. My these is that, at this time, online spam increased by an order of magnitude
  - TeaBrain 2y ago
    I don't think this is necessarily converse to what they said.
  - bobthepanda 2y ago
    Winning the war against spam is an arms race. Spam hasn’t spent years targeting AI search yet.
  - dageshi 2y ago
    I think it was the switch from desktop search traffic being dominant to mobile traffic being dominant, that switch happened around the end of 2016. Google used to prioritise big comprehensive articles on subjects for desktop users but mobile users just wanted quick answers, so that's what google prioritised as they became the biggest users. But also, per your point, I think those smaller simpler less comprehensive posts are easier to fake/spam than the larger more compreshensible posts that came before.
    - zeknife 2y ago
      Ironically, I almost never see quick answers in the top results, mostly it's dragged out pages of paragraph after paragraph with ads inbetween.
      - dartos 2y ago
        Guess who sells the ads…
  - state_less 2y ago
    Old style Google search is dead, folks just haven’t closed the casket yet. My index queries are down ~90%. In the future, we’ll look back at LLMs as a major turning point in how people retrieve and consume information.
    - darepublic 2y ago
      I still prefer it over using llm. And I would be doubtful that llm search has major benefits over Google search imo
      - ben_w 2y ago
        Depends what you want it for. Right now, I find each tool better at different things. If I can only describe what I want but don't know key words, LLM are the only solution. If I need citations, LLMs suck.
    - esafak 2y ago
      Abstractive vs. extractive search.
  - EVa5I7bHFq9mnYK 2y ago
    It's getting ridiculous. Half of the time now when I ask AI to search some information for me, it finds and summarizes some very long article obviously written by AI, and lacking any useful information.
  - th0ma5 2y ago
    Queries were rewritten with BERT starting even before then so it's still the same generative model problem.
- imiric 2y ago
  I recently tried to ask these tools for help with using a popular library, and both GPT-4o and Claude 3.5 Sonnet gave highly misleading and unusable suggestions. They consistently hallucinated APIs that didn't exist, and would repeat the same wrong answers, ignoring my previous instructions. I spent upwards of 30 minutes repeating "now I get this error" to try to coax them in the right direction, but always ending up in a loop that got me nowhere. Some of the errors were really basic too, like referencing a variable that was never declared, etc. Finally, Claude made a tangential suggestion that made me look into using a different approach, but it was still faster to look into the official documentation than to keep asking it questions. GPT-4o was noticeably worse, and I quickly abandoned it. If this is the state of the art of coding LLMs, I really don't see why I should waste my time evaluating their confident sounding, but wrong, answers. It doesn't seem like much has improved in the past year or so, and at this point this seems like an inherent limitation of the architecture.
  - geodel 2y ago
    Well it is volume business. <1% of advanced skill developers will find AI helper useless but for 99% of IT CRUD peddlers these tools are quite sufficient. All in all if employers cut down 15-20% of net development costs by reducing head counts, it will be very worthwhile for companies.
    - WgaqPdNr7PGLGVW 2y ago
      I suspect it will go a different direction. Codebases are exploding in size. Feature development has slowed down. What might have been a carefully designed 100kloc codebase in 2018 is now a 500kloc ball of mud in 2024. Companies need many more developers to complete a decent sized feature than they needed in 2018.
      - outworlder 2y ago
        It's worse than that. Now the balls of mud are distributed. We get incredibly complex interactions between services which need a lot of infrastructure to enable them, that requires more observability, which requires more infrastructure...
thelittleone 2y ago
I'm the same, but had a lot of issues getting structured output from Anthropic. Ended up always writing response processors. Frustrated by how fragile that was, decided to try OpenAI structured outputs and it just worked and since they also have prompt caching now, it worked out very well for my use case. Anthropic's seems to have addressed the issue using pydantic but I haven't had a chance to test it yet. I pretty much use Anthropic for everything else.
dangsux 2y ago
[dead]
JacobThreeThree 2y ago
>The second is with all the OpenAI drama MS has started to distance themselves over a souring relationship (allegedly). If so, this could be a smart move away tactfully. I agree, this was a tactical move designed to give them leverage over OpenAI.

dartos 2y ago

Yeah, Claude consistently impresses me. A commenter on another thread mentioned it but it’s very similar to how search felt in the early 2000s. I ask it a question and get my answer. Sometimes it’s a little (or a lot) wrong or outdated, but at least I get something to tinker with.

gonab 2y ago
Conversely I feel that the experience of searching has been degraded by a lot since 2016/17. My these is that, at this time, online spam increased by an order of magnitude
- TeaBrain 2y ago
  I don't think this is necessarily converse to what they said.
- bobthepanda 2y ago
  Winning the war against spam is an arms race. Spam hasn’t spent years targeting AI search yet.
- dageshi 2y ago
  I think it was the switch from desktop search traffic being dominant to mobile traffic being dominant, that switch happened around the end of 2016. Google used to prioritise big comprehensive articles on subjects for desktop users but mobile users just wanted quick answers, so that's what google prioritised as they became the biggest users. But also, per your point, I think those smaller simpler less comprehensive posts are easier to fake/spam than the larger more compreshensible posts that came before.
  - zeknife 2y ago
    Ironically, I almost never see quick answers in the top results, mostly it's dragged out pages of paragraph after paragraph with ads inbetween.
    - dartos 2y ago
      Guess who sells the ads…
- state_less 2y ago
  Old style Google search is dead, folks just haven’t closed the casket yet. My index queries are down ~90%. In the future, we’ll look back at LLMs as a major turning point in how people retrieve and consume information.
  - darepublic 2y ago
    I still prefer it over using llm. And I would be doubtful that llm search has major benefits over Google search imo
    - ben_w 2y ago
      Depends what you want it for. Right now, I find each tool better at different things. If I can only describe what I want but don't know key words, LLM are the only solution. If I need citations, LLMs suck.
  - esafak 2y ago
    Abstractive vs. extractive search.
- EVa5I7bHFq9mnYK 2y ago
  It's getting ridiculous. Half of the time now when I ask AI to search some information for me, it finds and summarizes some very long article obviously written by AI, and lacking any useful information.
- th0ma5 2y ago
  Queries were rewritten with BERT starting even before then so it's still the same generative model problem.
imiric 2y ago
I recently tried to ask these tools for help with using a popular library, and both GPT-4o and Claude 3.5 Sonnet gave highly misleading and unusable suggestions. They consistently hallucinated APIs that didn't exist, and would repeat the same wrong answers, ignoring my previous instructions. I spent upwards of 30 minutes repeating "now I get this error" to try to coax them in the right direction, but always ending up in a loop that got me nowhere. Some of the errors were really basic too, like referencing a variable that was never declared, etc. Finally, Claude made a tangential suggestion that made me look into using a different approach, but it was still faster to look into the official documentation than to keep asking it questions. GPT-4o was noticeably worse, and I quickly abandoned it. If this is the state of the art of coding LLMs, I really don't see why I should waste my time evaluating their confident sounding, but wrong, answers. It doesn't seem like much has improved in the past year or so, and at this point this seems like an inherent limitation of the architecture.
- geodel 2y ago
  Well it is volume business. <1% of advanced skill developers will find AI helper useless but for 99% of IT CRUD peddlers these tools are quite sufficient. All in all if employers cut down 15-20% of net development costs by reducing head counts, it will be very worthwhile for companies.
  - WgaqPdNr7PGLGVW 2y ago
    I suspect it will go a different direction. Codebases are exploding in size. Feature development has slowed down. What might have been a carefully designed 100kloc codebase in 2018 is now a 500kloc ball of mud in 2024. Companies need many more developers to complete a decent sized feature than they needed in 2018.
    - outworlder 2y ago
      It's worse than that. Now the balls of mud are distributed. We get incredibly complex interactions between services which need a lot of infrastructure to enable them, that requires more observability, which requires more infrastructure...

thelittleone 2y ago

I'm the same, but had a lot of issues getting structured output from Anthropic. Ended up always writing response processors. Frustrated by how fragile that was, decided to try OpenAI structured outputs and it just worked and since they also have prompt caching now, it worked out very well for my use case. Anthropic's seems to have addressed the issue using pydantic but I haven't had a chance to test it yet. I pretty much use Anthropic for everything else.

dangsux 2y ago

[dead]

JacobThreeThree 2y ago

>The second is with all the OpenAI drama MS has started to distance themselves over a souring relationship (allegedly). If so, this could be a smart move away tactfully. I agree, this was a tactical move designed to give them leverage over OpenAI.